A PERTURBATION-BASED APPROACH FOR MULTI-CLASSIFIER SYSTEM DESIGN
V. Lecce Di, Giovanni Dimauro, Alberto Refice, Stefano Vittorio Impedovo, Giuseppe Pirlo, Anna Eugenia Salzo · 2004
This paper presents a perturbationbased approach useful to select the best combination method for a multiclassifier system. The basic idea is to simulate small variations in the performance of the set of classifiers and to evaluate to what extent they influence the performance of the combined classifier. In the experimental phase, the Behavioural Knowledge Space and the DempsterShafer combination methods have been considered. The experimental results, carried out in the field of handwritten numeral recognition, demonstrate the effectiveness of the new approach